https://github.com/jalajthanaki/facial_emotion_recognition_using_tensorflow
I have used FER2013 dataset and try to build the Facial emotion recognition using TensorFlow
https://github.com/jalajthanaki/facial_emotion_recognition_using_tensorflow
convolutional-neural-networks facial-emotion-recognition tensorflow
Last synced: 5 months ago
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I have used FER2013 dataset and try to build the Facial emotion recognition using TensorFlow
- Host: GitHub
- URL: https://github.com/jalajthanaki/facial_emotion_recognition_using_tensorflow
- Owner: jalajthanaki
- Created: 2018-02-18T16:14:10.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-02-18T17:10:24.000Z (over 7 years ago)
- Last Synced: 2025-03-31T22:22:14.828Z (6 months ago)
- Topics: convolutional-neural-networks, facial-emotion-recognition, tensorflow
- Language: Python
- Size: 14.4 MB
- Stars: 4
- Watchers: 2
- Forks: 8
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
# Emotion recognition CNN based approach using TensorFlow
This repository is the out project about Face emotion recognition using convolutional neural network.
## Dependencies
- [NumPy](http://docs.scipy.org/doc/numpy-1.10.1/user/install.html)
- [Tensorflow](https://www.tensorflow.org/versions/r0.8/get_started/os_setup.html)
- [TFLearn](https://github.com/tflearn/tflearn#installation)
- [OpenCV](https://opencv-python-tutroals.readthedocs.io/en/latest/)
## Dataset
We use the [FER-2013 Faces Database](http://www.socsci.ru.nl:8180/RaFD2/RaFD?p=main), a set of 28,709 pictures of people displaying 7 emotional expressions (angry, disgusted, fearful, happy, sad, surprised and neutral).
You have to request for access to the dataset or you can get it on [Kraggle](https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge/data).
## Download per-trained model and data in numpy format from this link.
* Step 1: Download [data.zip](https://drive.google.com/open?id=1z74zDZDBbWOc_L62KYMbHT8McJ1vqFrw) file.
* Step 2: Unzip the files.
* Step 3: Paste all the files into the data folder of the repository
## Train
```bash
$ python emotion_recognition.py train
```
## Test
```bash
$ python emotion_recognition.py poc
```
## Paper
[Link](https://github.com/isseu/emotion-recognition-neural-networks/blob/master/paper/Report_NN.pdf)
## Credit
This code credit goes to [Enrique Correa](https://github.com/isseu). I've merely created a wrapper to get people started.